A Cost-Effective Solution for Non-Convex Economic Load Dispatch Problems in Power Systems Using Slime Mould Algorithm

Abstract

Slime Mould Algorithm (SMA) is a newly designed meat-heuristic search that mimics the nature of slime mould during the oscillation phase. This is demonstrated in a unique mathematical formulation that utilizes adjustable weights to influence the sequence of both negative and positive propagation waves to develop a method to link food supply with intensive exploration capacity and exploitation affinity. The study shows the usage of the SM algorithm to solve a non-convex and cost-effective Load Dispatch Problem (ELD) in an electric power system. The effectiveness of SMA is investigated for single area economic load dispatch on large-, medium-, and small-scale power systems, with 3-, 5-, 6-, 10-, 13-, 15-, 20-, 38-, and 40-unit test systems, and the results are substantiated by finding the difference between other well-known meta-heuristic algorithms. The SMA is more efficient than other standard, heuristic, and meta-heuristic search strategies in granting extremely ambitious outputs according to the comparison records.

Improved slime mould algorithm based on hybrid strategy optimization of Cauchy mutation and simulated annealing

“…Researchers have applied the slime mould algorithm and its variants to engineering optimization problems and other research fields. For example, solving single- and du-al-objective economic and emission scheduling (EED) problems considering valve point effects [ 34 ]; determining the best operating rules for complex hydropower multi-reservoir prediction problems [ 38 ]; distributed generation (DG) solution of distribution network reconfiguration (DNR) problem [ 39 ]; photovoltaic model optimization design (Lin, 2022); demand estimation of urban water resources problem [ 40 ]; feature selection [ 41 ]; Reliability optimization of micro-milling cutting parameters [ 42 ]; Opti-mal Power Flow Problem [ 43 ]; A Cost-Effective Solution for Non-Convex Economic Load Dispatch Problems in Power Systems [ 44 ]; path planning and obstacle avoidance problem in mobile robots [ 45 ], optimal load-shedding in distribution system problem [ 30 ], etc.…”

Economic Load Dispatch Problem Based on Search and Rescue Optimization Algorithm

“…In [25], authors have used a data mining-based approach for solving multi-objective ELD. In [26], authors have used nonconvex ELD problem by Slime Mould Algorithm (SMA). In [27], authors have proposed an adaptive version of Class Topper Optimization (CTO) along with the incorporation of chaos theory for solving ELD, EED, and CEED.…”

Enhanced Teaching Learning-Based Algorithm for Fuel Costs and Losses Minimization in AC-DC Systems

“…Optimal power flow and economic dispatch (ED) seem to be crucial minimization aspects in power systems that necessitate efficient generator interoperability, strategic planning, and scheduling [2]. In [3], a slime mould technique driven by customizable weight vector to control the series among positive and negative propagation waves was utilized for the minimized ED problem. In [4], a bi-stage self-adaptive differential evolution (DE) approach of k-nearest neighbours relying computation system has been designed to address numerous metaheuristic issues, and it was suggested that the ED problem be addressed in the upcoming years.…”